Contributor: Chi Zhang
Reading list
survey/review/perspective paper book
Required
- Dark, Beyond Deep: A Paradigm Shift to Cognitive AI with Humanlike Common Sense (Section 8), Engineering 2020
- The structure-mapping engine: Algorithm and examples, Artificial Intelligence 1989
- Mental models and human reasoning, PNAS 2010
- On the Measure of Intelligence, arXiv preprint arXiv:1911.01547
- Human-level concept learning through probabilistic program induction, Science 2015
- Psychological Reasoning in Infancy, Annual Review of Psychology 2016
- Abstraction and analogy-making in artificial intelligence, Annals of the New York Academy of Sciences 2021
- The Perception of Relations, TiCS 2021
Optional
- Rule Learning by Seven-Month-Old Infants, Science 1999
- The Origin of Concepts, Oxford University Press (2009)
- Bayesian Models of Conceptual Development: Learning as Building Models of the World, Annual Review of Developmental Psychology 2020
- Scientific Thinking in Young Children: Theoretical Advances, Empirical Research, and Policy Implications, Science 2012
- Very young infants learn abstract rules in the visual modality, PLOS One 2017
Optional - Raven’s Progressive Matrices (Spatial-Temporal)
- What One Intelligence Test Measures: A Theoretical Account of the Processing in the Raven Progressive Matrices Tes, PsychReview 1990
- RAVEN: A Dataset for Relational and Analogical Visual Reasoning, CVPR 2019
- Measuring abstract reasoning in neural networks, ICML 2018
- Learning Perceptual Inference by Contrasting, NeurIPS 2019
- Abstract Diagrammatic Reasoning with Multiplex Graph Networks, ICLR 2020
- Abstract Spatial-Temporal Reasoning via Probabilistic Abduction and Execution, CVPR 2021
- Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning, ECCV 2022
Optional - Abstraction and Concept Learning
- How to Grow a Mind: Statistics, Structure, and Abstraction, Science 2011
- DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning, PLDI 2021
- The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision, ICLR 2019
- Human-like systematic generalization through a meta-learning neural network, Nature 2023
- Human-like Few-Shot Learning via Bayesian Reasoning over Natural Language, NeurIPS 2023
- Learning Algebraic Representation for Systematic Generalization in Abstract Reasoning, ECCV 2022
- HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving, arXiv preprint arXiv:2102.11344
Optional - Blicket Detection (Causal)
- Detecting Blickets: How Young Children Use Information about Novel Causal Powers in Categorization and Induction, Child Development 2000
- When children are better (or at least more open-minded) learners than adults: Developmental differences in learning the forms of causal relationships, Cognition 2014
- ACRE: Abstract Causal Reasoning Beyond Covariation, CVPR 2021
Optional - Number Sense
- Core systems of number, TiCS 2004
- Abstract number and arithmetic in preschool children, PNAS 2005
- Newborn infants perceive abstract numbers, PNAS 2009
- Number without a language model, PNAS 2010
- Representations of space, time, and number in neonates, PNAS 2014
- Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning, AAAI 2020
- Verbal counting and the timing of number acquisition in an indigenous Amazonian group, PLOS One 2022
Optional - Neuro-symbolic Reasoning
- Continuous Relaxation of Symbolic Planner for One-Shot Imitation Learning, IROS 2019
- Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding, NeurIPS 2018
- The Neuro-Symbolic Concept Learner: Interpreting Scenes, Words, and Sentences From Natural Supervision, ICLR 2019
- Picture: A Probabilistic Programming Language for Scene Perception, CVPR 2015
- DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning, PLDI 2021
- Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning, ICML 2020
Optional - Differential Optimization
- Differentiable Convex Optimization Layers, NeurIPS 2019
- OptNet: Differentiable Optimization as a Layer in Neural Networks, ICML 2017
- On Differentiating Parameterized Argmin and Argmax Problems with Application to Bi-level Optimization, arXiv preprint arXiv:1607.05447
Essay
Discuss in your opinion what is reasoning, how humans perform the task of reasoning in daily life, what is an ideal task for evaluating the general reasoning capability and, if it is abstract, how different aspects of it are reflected in real world and the potential computational model.